# last-map-probs

This script reads alignments of DNA reads to a genome, and estimates the probability that each alignment represents the genomic source of the read.

It writes the alignments with "mismap" probabilities, i.e. the probability that the alignment does not represent the genomic source of the read. By default, it discards alignments with mismap probability > 0.01.

## Typical usage

These commands map DNA reads to the human genome:

    lastdb -uNEAR -R01 hu human/chr*.fa
    lastal -Q1 -D1000 hu reads.fastq | last-map-probs > myalns.maf

## Options

> `-h, --help` | Show a help message, with default option values, and exit.
> `-m M, --mismap=M` | Don't write alignments with mismap probability > M. Low-confidence alignments will be discarded unless you increase this value!
> `-s S, --score=S` | Don't write alignments with score < S. The default value is somewhat higher than the lastal score threshold. Specifically, it is e + t * ln(1000), where e is the score threshold, and t is a scale factor that is written in the lastal header. This roughly means that, for every alignment it writes, it has considered alternative alignments with one-thousandth the probability.

## Details

- This script can read alignments in either of the formats produced by lastal (maf or tabular).

- The script reads one batch of alignments at a time (by looking for lines starting with "# batch"). If the batches are huge (e.g. because there are no lines starting with "# batch"), it might need too much memory.

## Using multiple CPUs

This will run the pipeline on all your CPU cores:

    parallel-fastq "lastal -Q1 -D1000 hu | last-map-probs" < reads.fastq > myalns.maf

It requires GNU parallel to be installed (http://www.gnu.org/software/parallel/).

## Limitations

- It is possible that two or more alignments reflect the origin of one query sequence, for instance if the query arose by splicing. This script makes no allowance for that possibility.

## Method

Suppose one query sequence has three alignments, with scores: s1, s2, s3. The probability that the first alignment is the one that reflects the origin of the query, is:

    exp(s1/t) / [exp(s1/t) + exp(s2/t) + exp(s3/t)]

Here, t is a parameter that depends on the scoring scheme: it is written in the lastal header.

## Reference

For more information, please see this article:

> Incorporating sequence quality data into alignment improves DNA read mapping. Frith MC, Wan R, Horton P. Nucleic Acids Research 2010 38:e100.